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找到约 5,352 项符合「Learning」的源代码

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www.eeworm.com/read/339665/12211206

m demolgd1.m

%DEMOLGD1 Demonstrate simple MLP optimisation with on-line gradient descent % % Description % The problem consists of one input variable X and one target variable % T with data generated by sampling X
www.eeworm.com/read/150905/12248251

m ffnc.m

%FFNC Feed-forward neural net classifier back-end % % [W,HIST] = FFNC (ALG,A,UNITS,ITER,W_INI,T,FID) % % INPUT % ALG Training algorithm: 'bpxnc' for back-propagation (default), 'lmnc' %
www.eeworm.com/read/150905/12249878

m demolgd1.m

%DEMOLGD1 Demonstrate simple MLP optimisation with on-line gradient descent % % Description % The problem consists of one input variable X and one target variable % T with data generated by sampling X
www.eeworm.com/read/251685/12325930

m chap4_1.m

%Single Neural Adaptive PID Controller clear all; close all; x=[0,0,0]'; xiteP=0.40; xiteI=0.35; xiteD=0.40; %Initilizing kp,ki and kd wkp_1=0.10; wki_1=0.10; wkd_1=0.10; %wkp_1=rand;
www.eeworm.com/read/149739/12352639

m ffnc.m

%FFNC Feed-forward neural net classifier back-end % % [W,HIST] = FFNC (ALG,A,UNITS,ITER,W_INI,T,FID) % % INPUT % ALG Training algorithm: 'bpxnc' for back-propagation (default), 'lmnc' %
www.eeworm.com/read/149474/12376199

hpp bpnet.hpp

//Header: BPNet.hpp //Language: Borland C++ 3.1 //Version: 1.0 //Environ: Any //Author: Liu Kang //Date: 3/1996 //Purpose: Provide a class for BP neural network #ifndef __BPNET__HPP #defin
www.eeworm.com/read/336314/12451564

m contents.m

% Neural Network Design Demonstrations. % Copyright (c) 1994 by PWS Publishing Company. % % General % nnd - Splash screen. % nndtoc - Table of contents. % nnsound - Turn Neural Net
www.eeworm.com/read/148489/12463536

m chap4_1.m

%Single Neural Adaptive PID Controller clear all; close all; x=[0,0,0]'; xiteP=0.40; xiteI=0.35; xiteD=0.40; %Initilizing kp,ki and kd wkp_1=0.10; wki_1=0.10; wkd_1=0.10; %wkp_1=rand;
www.eeworm.com/read/232951/14175846

m chap4_1.m

%Single Neural Adaptive PID Controller clear all; close all; x=[0,0,0]'; xiteP=0.40; xiteI=0.35; xiteD=0.40; %Initilizing kp,ki and kd wkp_1=0.10; wki_1=0.10; wkd_1=0.10; %wkp_1=rand;
www.eeworm.com/read/130698/14177598

m contents.m

% Neural Network Design Demonstrations. % Copyright (c) 1994 by PWS Publishing Company. % % General % nnd - Splash screen. % nndtoc - Table of contents. % nnsound - Turn Neural Net